Transverse Lattice QCD in 2+1 Dimensions

Following a suggestion due to Bardeen and Pearson, we formulate an effective light-front Hamiltonian for large-N gauge theory in (2+1)-dimensions. Two space-time dimensions are continuous and the remaining space dimension is discretised on a lattice. Eguchi-Kawai reduction to a (1+1)-dimensional theory takes place. We investigate the string tension and glueball spectrum, comparing with Euclidean Lattice Monte Carlo data.Comment: 4 pages LaTeX with 2 Postscript figures, uses boxedeps.tex and e spcrc2.sty. Poster session contribution to LATTICE96(poster). Minor changes in new versio

Convergence of Discretized Light Cone Quantization in the small mass limit

I discuss the slow convergence of Discretized Light Cone Quantization (DLCQ) in the small mass limit and suggest a solution.Comment: 8 pages, 5 Postscript figures, uses boxedeps.te

Adaptive Feature Selection for Object Tracking with Particle Filter

International audienceObject tracking is an important topic in the field of computer vision. Commonly used color-based trackers are based on a fixed set of color features such as RGB or HSV and, as a result, fail to adapt to changing illumination conditions and background clutter. These drawbacks can be overcome to an extent by using an adaptive framework which selects for each frame of a sequence the features that best discriminate the object from the background. In this paper, we use such an adaptive feature selection method embedded into a particle filter mechanism and show that our tracking method is robust to lighting changes and background distractions. Different experiments also show that the proposed method outperform other approaches

Colour-Dielectric Gauge Theory on a Transverse Lattice

We investigate in some detail consequences of the effective colour-dielectric formulation of lattice gauge theory using the light-cone Hamiltonian formalism with a transverse lattice. As a quantitative test of this approach, we have performed extensive analytic and numerical calculations for 2+1-dimensional pure gauge theory in the large N limit. Because of Eguchi-Kawai reduction, one effectively studies a 1+1-dimensional gauge theory coupled to matter in the adjoint representation. We study the structure of coupling constant space for our effective potential by comparing with the physical results available from conventional Euclidean lattice Monte Carlo simulations of this system. In particular, we calculate and measure the scaling behaviour of the entire low-lying glueball spectrum, glueball wavefunctions, string tension, asymptotic density of states, and deconfining temperature. We employ a new hybrid DLCQ/wavefunction basis in our calculations of the light-cone Hamiltonian matrix elements, along with extrapolation in Tamm-Dancoff truncation, significantly reducing numerical errors. Finally we discuss, in light of our results, what further measurements and calculations could be made in order to systematically remove lattice spacing dependence from our effective potential a priori.Comment: 48 pages, Latex, uses macro boxedeps.tex, minor errors corrected in revised versio

ImageNet Large Scale Visual Recognition Challenge

The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images. The challenge has been run annually from 2010 to present, attracting participation from more than fifty institutions. This paper describes the creation of this benchmark dataset and the advances in object recognition that have been possible as a result. We discuss the challenges of collecting large-scale ground truth annotation, highlight key breakthroughs in categorical object recognition, provide a detailed analysis of the current state of the field of large-scale image classification and object detection, and compare the state-of-the-art computer vision accuracy with human accuracy. We conclude with lessons learned in the five years of the challenge, and propose future directions and improvements.Comment: 43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional reference

Нарративное интервью в исследовании катамнеза внутренней картины болезни при шизофрении (клинико-психологический аспект)

Представлены особенности проведения клинического нарративного интервью как значимого метода в психодиагностике внутренней картины болезни (ВКБ) в катамнезе у больных шизофренией. Проведено комплексное психоанамнестическое, психодиагностическое, патоперсонологическое обследование больных параноидной шизофренией. Сформулированы стратегии и тактики проведения нарративного интервью с целью выявления особенностей их ВКБ.Наведено особливості проведення клінічного наративного інтерв'ю як визначального методу в психодіагностиці внутрішньої картини хвороби (ВКХ) у катамнезі у хворих на шизофренію. Проведено комплексне психоанамнестичне, психодіагностичне, патоперсонологічне обстеження хворих на параноїдну шизофренію. Сформульовано стратегії і тактики проведення наративного інтерв'ю з метою виявлення особливостей їх ВКХ.The peculiarities of clinical narrative interview as a significant method in psychodagnosis of the disease inner picture (DIP) in the history of patients with schizophrenia are presented. Complex psychoanamnestic, psychodiagnostic, pathopersonological investigation of patients with paranoid schizophrenia was performed. The strategies and tactics of narrative interview with the purpose to reveal DIP peculiarities were formulated